RouterBase API Integration

Overview

Use routerbase as an OpenAI-compatible gateway for GPT, Claude, Gemini, and other supported models. This skill helps agents migrate existing OpenAI-compatible code, keep API keys server-side, and produce concise, testable RouterBase integration snippets.

Read references/routerbase-api.md when exact endpoint details, headers, or examples are needed.

Integration Workflow

1. Identify whether the user is asking for migration, a new integration, debugging, or documentation.
2. Keep credentials out of client/browser code. Prefer ROUTERBASE_API_KEY in server-side environment configuration.
3. Reuse the user's existing OpenAI-compatible client when possible. Change the base URL to https://routerbase.com/v1, then swap the model to a RouterBase model ID.
4. Preserve standard OpenAI request shapes unless RouterBase docs or the selected model require a model-specific field.
5. For model IDs, use the live model catalog when an API key is available; otherwise use documented examples only as a starting point and tell the user to verify current availability.
6. Add a minimal smoke test, but do not run it unless credentials are present and the user expects a live API call.

Common Patterns

Python

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["ROUTERBASE_API_KEY"],
    base_url="https://routerbase.com/v1",
)

response = client.chat.completions.create(
    model="google/gemini-2.5-flash",
    messages=[{"role": "user", "content": "Write one sentence about model routing."}],
)

print(response.choices[0].message.content)

JavaScript

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.ROUTERBASE_API_KEY,
  baseURL: "https://routerbase.com/v1",
});

const response = await client.chat.completions.create({
  model: "google/gemini-2.5-flash",
  messages: [{ role: "user", content: "Write one sentence about model routing." }],
});

console.log(response.choices[0].message.content);

curl

curl -X POST https://routerbase.com/v1/chat/completions \
  -H "Authorization: Bearer $ROUTERBASE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "google/gemini-2.5-flash",
    "messages": [{"role": "user", "content": "What is 2+2?"}]
  }'

Implementation Guardrails

• Never paste or log real API keys. Use placeholders like sk-rb-... only in docs.
• Never put RouterBase keys in browser, mobile, or public repository code.
• Keep examples OpenAI-compatible unless the user asks for a framework-specific adapter.
• For streaming, set stream: true and process Server-Sent Events or SDK stream chunks.
• For tool calling and JSON mode, keep the standard OpenAI fields tools and response_format.
• For multimodal chat, use OpenAI content parts with text and image_url.
• If a live request fails, check headers, model ID, endpoint path, rate limits, and account access before changing application logic.

Output Checklist

• Include the changed base URL.
• Include where ROUTERBASE_API_KEY should be configured.
• Include one minimal request example.
• Include a clear note when model IDs or prices should be checked against the live RouterBase catalog.
• Include a test command or dry-run validation path.